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BRJ – Volume 61, Number 1, 2014
Mojtaba Maghrebi, Claude Sammut and Travis S. Waller:
Predicting the duration of concrete operations via artificial neural network
and by focusing on supply chain parameters . . . . . . . . . . . . . . . . . . . . . . 1 – 14
Alexander Tesar, Jozef Melcer and Daniela Kucharova:
Monitoring of small channel slabs in railway track science . . . . . . . . . . . . . 15 – 24
Ibrahim M. Metwally:
Intelligent predicting system for modeling of flexurally
– strengthened reinforced concrete beams with CFRP laminates . . . . . . . . . 25 – 42
Alaa M. Rashad and Hosam.El Din H. Seleem:
A study on high strength concrete with moderate cement content incorporating limestone powder . . . . . 43 – 58
Tejwant Singh Brar and Navneet Munoth:
Solar and green building guidelines for hot arid climate in India . . . . . . . . . . . . . 59 – 65
Abstracts
Predicting the duration of concrete operations via artificial neural network and by focusing on supply chain parameters
Mojtaba Maghrebi, Claude Sammut and Travis S. Waller
Being able to precisely predict the duration of concrete operations can help construction managers to organize sites and machineries more efficiently, especially when there is limited space for equipment on site. Currently there is no theoretical method for estimating the duration of the concrete pouring process. Normally, the maximum capacity of pumping facilities on construction sites is not used, and concrete pumps are idle for a considerable time as a result of the arrival of concrete trucks being delayed. In the light of this issue, this paper considers the supply chain parameters of Ready Mixed Concrete (RMC) as a means of solving this problem. Artificial Neural Network (ANN) is hired for modelling/predicting the productivity of a concrete operation. The proposed model is tested with a real database of an RMC in the Sydney metropolitan area that has 17 depots and around 200 trucks. Results show that there is an improvement in the achieved results when these are compared to the results of relevant studies that only considered the construction parameters for predicting the productivity of concrete operations.
Keywords: RMC, productivity, supply chain
Monitoring of small channel slabs in railway track science
Alexander Tesar, Jozef Melcer and Daniela Kucharova
Presented is the adoption of fractal approaches for identification and monitoring of small channel slabs in advanced railway track science. The assessment of the problem is presented. The analysis is based on wave approaches. Some structural applications and testing in situ are submitted.
Keywords: fractals, identification, monitoring, structural response, small channel slab, testing, wave approach
Intelligent predicting system for modeling of flexurally – strengthened reinforced concrete beams with CFRP laminates
Ibrahim M. Metwally
In the last years, a great number of experimental tests have been performed to determine the ultimate strength of reinforced concrete (RC) beams retrofitted in flexure by means of externally bonded carbon fiber-reinforced polymers (CFRP). Most of design proposals for flexural strengthening are based on a regression analysis from experimental data corresponding to specific configurations which makes it very difficult to capture the real interrelation among the involved parameters. To avoid this, an intelligent predicting system such as artificial neural network (ANN) has been developed to predict the flexural capacity of concrete beams reinforced with this method. An artificial neural network model was developed using past experimental data on flexural failure of RC beams strengthened by CFRP laminates. Fourteen input parameters cover the CFRP properties, beam geometrical properties and reinforcement properties; the corresponding output is the ultimate load capacity. The proposed ANN model considers the effect of these parameters which are not generally account together in the current existing design codes with the purpose of reaching more reliable designs. This paper presents a short review of the well-known American building code provisions (ACI 440.2R-08) for the flexural strengthening of RC beams using FRP laminates. The accuracy of the code in predicting the flexural capacity of strengthened beams was also examined with comparable way by using same test data. The study shows that the ANN model gives reasonable predictions of the ultimate flexural strength of the strengthened RC beams. Moreover, the study concludes that the ANN model predicts the flexural strength of FRP-strengthened beams better than the design formulas provided by ACI 440.
Keywords: CFRP laminates, RC beam, flexural capacity, neural networks, ACI 440
A study on high strength concrete with moderate cement content incorporating limestone powder
Alaa M. Rashad and Hosam.El Din H. Seleem
This paper presents the results of an investigation to assess the validity of producing high strength concrete (HSC) using moderate cement content to reduce the consumption of the binders. Cement content is lowered from 500 kg/m3 to 400 kg/m3. The difference in cement content is compensated by the addition of fine limestone (LS) powder. Pozzolans were incorporated as an addition to cement. Different coarse aggregate types were employed. Workability, compressive strength, tensile strength, permeability and drying shrinkage were measured. Test results revealed that HSC with a compressive strength up to 79 MPa (at 90 days age) could be produced with moderate cement content. The mixtures consistency and drying shrinkage are greatly enhanced due to employing LS powder and the permeability is satisfactory. To provide better solution to some concrete disadvantages like cracking and drying shrinkage, using an economic rate for cement are believed to reduce these disadvantages.
Keywords: high strength, cement content, pozzolan, limestone powder, concrete proportioning
Solar and green building guidelines for hot arid climate in India
Tejwant Singh Brar and Navneet Munoth
There are, presently, two schools of thought when it comes to designing buildings that promote sustainable development. One school emphasizes materials use and ‘‘green’’ buildings, while the other emphasizes energy use and energy efficient buildings. The promoters of ‘‘green’’ buildings often claim that the reduced energy use during operation of the low energy and solar buildings is counteracted by the increased embodied energy in these buildings. This paper gives categorical analysis of the technologies available for Low energy and green architecture and emphasizes the need to integrate both in residential buildings to of lower the energy use in operation during the lifetime in a residential building in hot arid climate. The results also show that there should be little difference between the approaches of the two schools of thought. The best buildings will generally be those that are both low energy, and ‘‘green’’. This paper also gives policy guidelines to integrate them in the building bye-laws for hot arid climate.
Keywords: green architecture, green buildings, solar architecture, hot arid climate, low energy intensive materials, orientation of building, building bye-laws